/tmp/ipykernel_14678/3287265490.py:1: DtypeWarning:
Columns (4,5,6,8) have mixed types. Specify dtype option on import or set low_memory=False.
ds
unique_id
y
2022-01-01 00:00:00
ZONA
1707.0
2022-01-01 01:00:00
ZONA
1673.0
2022-01-01 02:00:00
ZONA
1644.0
2022-01-01 03:00:00
ZONA
1605.0
2022-01-01 04:00:00
ZONA
1550.0
2022-01-01 05:00:00
ZONA
1487.0
2022-01-01 06:00:00
ZONA
1422.0
2022-01-01 07:00:00
ZONA
1373.0
2022-01-01 08:00:00
ZONA
1336.0
2022-01-01 09:00:00
ZONA
1317.0
fig = go.Figure()for i in ts["unique_id"].unique(): d =None d = ts[ts["unique_id"] == i] name = i, fig.add_trace(go.Scatter(x=d["ds"], y=d["y"], name = i, mode='lines'))fig.update_layout(title ="The Hourly Demand for Electricity in New York by Independent System Operator")fig
fig = plot_series(ts, max_ids=len(ts.unique_id.unique()), plot_random=False, max_insample_length=24*30,engine ="plotly")fig.update_layout(title ="The Hourly Demand for Electricity in New York by Independent System Operator")fig
[LightGBM] [Info] Auto-choosing row-wise multi-threading, the overhead of testing was 0.001556 seconds.
You can set `force_row_wise=true` to remove the overhead.
And if memory is not enough, you can set `force_col_wise=true`.
[LightGBM] [Info] Total Bins 828
[LightGBM] [Info] Number of data points in the train set: 271689, number of used features: 6
[LightGBM] [Info] Start training from score 1559.341170
[LightGBM] [Info] Auto-choosing row-wise multi-threading, the overhead of testing was 0.001690 seconds.
You can set `force_row_wise=true` to remove the overhead.
And if memory is not enough, you can set `force_col_wise=true`.
[LightGBM] [Info] Total Bins 828
[LightGBM] [Info] Number of data points in the train set: 273009, number of used features: 6
[LightGBM] [Info] Start training from score 1558.672466
[LightGBM] [Info] Auto-choosing row-wise multi-threading, the overhead of testing was 0.001713 seconds.
You can set `force_row_wise=true` to remove the overhead.
And if memory is not enough, you can set `force_col_wise=true`.
[LightGBM] [Info] Total Bins 828
[LightGBM] [Info] Number of data points in the train set: 271953, number of used features: 6
[LightGBM] [Info] Start training from score 1559.180763
[LightGBM] [Info] Auto-choosing row-wise multi-threading, the overhead of testing was 0.002363 seconds.
You can set `force_row_wise=true` to remove the overhead.
And if memory is not enough, you can set `force_col_wise=true`.
[LightGBM] [Info] Total Bins 828
[LightGBM] [Info] Number of data points in the train set: 273273, number of used features: 6
[LightGBM] [Info] Start training from score 1558.428631
/workspaces/pydata-ny-ga-workshop/experimentation/backtesting.py:35: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
/workspaces/pydata-ny-ga-workshop/experimentation/backtesting.py:36: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
/workspaces/pydata-ny-ga-workshop/experimentation/backtesting.py:37: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
/workspaces/pydata-ny-ga-workshop/experimentation/backtesting.py:38: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
/workspaces/pydata-ny-ga-workshop/experimentation/backtesting.py:35: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
/workspaces/pydata-ny-ga-workshop/experimentation/backtesting.py:36: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
/workspaces/pydata-ny-ga-workshop/experimentation/backtesting.py:37: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
/workspaces/pydata-ny-ga-workshop/experimentation/backtesting.py:38: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
/workspaces/pydata-ny-ga-workshop/experimentation/backtesting.py:35: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
/workspaces/pydata-ny-ga-workshop/experimentation/backtesting.py:36: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
/workspaces/pydata-ny-ga-workshop/experimentation/backtesting.py:37: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
/workspaces/pydata-ny-ga-workshop/experimentation/backtesting.py:38: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
[LightGBM] [Info] Auto-choosing row-wise multi-threading, the overhead of testing was 0.004364 seconds.
You can set `force_row_wise=true` to remove the overhead.
And if memory is not enough, you can set `force_col_wise=true`.
[LightGBM] [Info] Total Bins 6438
[LightGBM] [Info] Number of data points in the train set: 271689, number of used features: 28
[LightGBM] [Info] Start training from score 1559.341170
[LightGBM] [Info] Auto-choosing row-wise multi-threading, the overhead of testing was 0.003561 seconds.
You can set `force_row_wise=true` to remove the overhead.
And if memory is not enough, you can set `force_col_wise=true`.
[LightGBM] [Info] Total Bins 6438
[LightGBM] [Info] Number of data points in the train set: 273009, number of used features: 28
[LightGBM] [Info] Start training from score 1558.672466
[LightGBM] [Info] Auto-choosing row-wise multi-threading, the overhead of testing was 0.003766 seconds.
You can set `force_row_wise=true` to remove the overhead.
And if memory is not enough, you can set `force_col_wise=true`.
[LightGBM] [Info] Total Bins 6438
[LightGBM] [Info] Number of data points in the train set: 271953, number of used features: 28
[LightGBM] [Info] Start training from score 1559.180763
[LightGBM] [Info] Auto-choosing row-wise multi-threading, the overhead of testing was 0.003832 seconds.
You can set `force_row_wise=true` to remove the overhead.
And if memory is not enough, you can set `force_col_wise=true`.
[LightGBM] [Info] Total Bins 6438
[LightGBM] [Info] Number of data points in the train set: 273273, number of used features: 28
[LightGBM] [Info] Start training from score 1558.428631
/workspaces/pydata-ny-ga-workshop/experimentation/backtesting.py:35: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
/workspaces/pydata-ny-ga-workshop/experimentation/backtesting.py:36: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
/workspaces/pydata-ny-ga-workshop/experimentation/backtesting.py:37: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
/workspaces/pydata-ny-ga-workshop/experimentation/backtesting.py:38: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
/workspaces/pydata-ny-ga-workshop/experimentation/backtesting.py:35: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
/workspaces/pydata-ny-ga-workshop/experimentation/backtesting.py:36: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
/workspaces/pydata-ny-ga-workshop/experimentation/backtesting.py:37: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
/workspaces/pydata-ny-ga-workshop/experimentation/backtesting.py:38: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
/workspaces/pydata-ny-ga-workshop/experimentation/backtesting.py:35: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
/workspaces/pydata-ny-ga-workshop/experimentation/backtesting.py:36: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
/workspaces/pydata-ny-ga-workshop/experimentation/backtesting.py:37: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
/workspaces/pydata-ny-ga-workshop/experimentation/backtesting.py:38: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy